I'll survey some of the algorithms and frameworks that have been developed for quantifying uncertainty (via confidence intervals, p-values, and the like) in inferences from differentially private releases. I'll draw parallels and contrasts with similar problems that were studied previously in statistics, and outline some major challenges for future work.